Disassociation for electronic health record privacy

Loukides, Grigorios ORCID: https://orcid.org/0000-0003-0888-5061, Liagouris, John, Gkoulalas-Divanis, Aris and Terrovitis, Manolis 2014. Disassociation for electronic health record privacy. Journal of Biomedical Informatics 50 , pp. 46-61. 10.1016/j.jbi.2014.05.009

Preview

PDF - Submitted Pre-Print Version Download (325kB) | Preview

Abstract

The dissemination of Electronic Health Record (EHR) data, beyond the originating healthcare institutions, can enable large-scale, low-cost medical studies that have the potential to improve public health. Thus, funding bodies, such as the National Institutes of Health (NIH) in the U.S., encourage or require the dissemination of EHR data, and a growing number of innovative medical investigations are being performed using such data. However, simply disseminating EHR data, after removing identifying information, may risk privacy, as patients can still be linked with their record, based on diagnosis codes. This paper proposes the first approach that prevents this type of data linkage using disassociation, an operation that transforms records by splitting them into carefully selected subsets. Our approach preserves privacy with significantly lower data utility loss than existing methods and does not require data owners to specify diagnosis codes that may lead to identity disclosure, as these methods do. Consequently, it can be employed when data need to be shared broadly and be used in studies, beyond the intended ones. Through extensive experiments using EHR data, we demonstrate that our method can construct data that are highly useful for supporting various types of clinical case count studies and general medical analysis tasks.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software R Medicine > RA Public aspects of medicine
Uncontrolled Keywords:	Privacy; Electronic health records; Disassociation; Diagnosis codes
Publisher:	Elsevier
ISSN:	1532-0464
Date of Acceptance:	16 May 2014
Last Modified:	02 Dec 2024 02:00
URI:	https://orca.cardiff.ac.uk/id/eprint/89585

Citation Data

Cited 20 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item